Unconstrained Offline Handwritten Word Recognition by Position Embedding Integrated ResNets Model

Wu, Xiang-Ping; Chen, Qingcai; You, Jane; Xiao, Yulun

doi:10.1109/lsp.2019.2895967

Cited by 26 publications

(8 citation statements)

References 35 publications

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“…g False Discovery Rate and False Omission Rate False Discovery Rate (FDR) and False Omission Rate are defined as per Eqs. (40) and (41). The MCC is a correlation coefficient between the observed and predicted binary classifications, it ranges the value between −1 and + 1.…”

Section: (A) Accuracymentioning

confidence: 99%

“…After the introduction of the digital content, it is more crucial for the researchers to develop a high-performance OCR engine with machine learning technology to analyze the document image by means of dividing the pages of the digital images into line elements and thereby sub-dividing into words and then to characters. The recognition of character is the most challenging as well as a tantalizing field with respect to diverse languages, as it varies from person to person on the state of mood [19,31,40].…”

Section: Introductionmentioning

confidence: 99%

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Optimally configured convolutional neural network for Tamil Handwritten Character Recognition by improved lion optimization model

Lincy

Gayathri

2020

Multimed Tools Appl

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In recent data, Optical character recognition (OCR) systems have laid hands in the field of most popular language recognitions. Unlike other languages, the Tamil language is more complex to recognize, and hence considerable efforts have been laid in literature. However, the models are not yet well-organized for precise recognition of Tamil characters. Thus, the current research work develops a novel Tamil Handwritten Character Recognition approach by following two major processes, viz. pre-processing and recognition. The pre-processing phase encloses RGB to grayscale conversion, binarization with thresholding, image complementation, morphological operations, and linearization. Subsequently, the pre-processed image after linearization is subjected to recognition via an optimally configured Convolutional Neural Network (CNN). More particularly, the fully connected layer and weights are fine-tuned by a new Self Adaptive Lion Algorithm (SALA) that is the conceptual improvement of the standard Lion Algorithm (LA). The performance of the proposed work is compared and proved over other state-of-the-art models with respect to certain performance measures.

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Section: (A) Accuracymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimally configured convolutional neural network for Tamil Handwritten Character Recognition by improved lion optimization model

Lincy

Gayathri

2020

Multimed Tools Appl

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“…The development of mobile Artificial Intelligence (AI) and Machine Learning (ML) applications lead to the advancement of the hardware for user equipment (UE) [1]. Although nowadays, some AI applicat ions, e.g., ResNet [2] and MobileNet [3] may be handled by UEs locally, other computational-intensive applications, e.g., augmented reality (AR) [4] services may still require to be processed in the central cloud. However, cloud normally requires mobile users to upload the tasks data before they can be processed.…”

Section: Introductionmentioning

confidence: 99%

Joint Program Partitioning and Resource Allocation for Completion Time Minimization in Multi-MEC Systems

Taizhou

Zhang

Wang

et al. 2022

IEEE Trans. Netw. Sci. Eng.

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This paper considers a practical mobile edge computing (MEC) system, where edge server does not preinstall the program required to perform user offloaded computing tasks. A partial program offloading (PPO) scheme is proposed, which can divide a user program into two parts, where the first part is executed by the user itself and the second part is transferred to an edge server for remote execution. However, the execution of the latter part requires the results of the previous part (called intermediate result) as the input. We aim to minimize the overall time consumption of a multi-server MEC system to complete all user offloaded tasks. It is modeled as a mixed integer nonlinear programming (MINLP) problem which considers user-and-server association, program partitioning, and communication resource allocation in a joint manner. An effective algorithm is developed to solve the problem by exploiting its structural features. First, the task completion time of a single server is minimized given the computing workload and available resource. Then, the working time of the edge servers are balanced by updating user-and-server association and communication resource allocation. Numerical results show that significant performance improvement can be achieved by the proposed scheme.

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“…Text recognition is the process of converting the text in one or more images into documents such as those written on a computer [1][2][3]. Currently, the word recognition problem has been studied and widely used in the automation of office operations in many languages like English [4,5], Chinese [6,7], Japanese [8]. In Vietnam, there are some identification systems such as VietOCR software [9] and VNDOCR [10].…”

Section: Introductionmentioning

confidence: 99%

Vietnamese character recognition based on CNN model with reduced character classes

2021

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This article will detail the steps to build and train the convolutional neural network (CNN) model for Vietnamese character recognition in educational books. Based on this model, a mobile application for extracting text content from images in Vietnamese textbooks was built using OpenCV and Canny edge detection algorithm. There are 178 characters classes in Vietnamese with accents. However, within the scope of Vietnamese character recognition in textbooks, some classes of characters only differ in terms of actual sizes, such as “c” and “C”, “o” and “O”. Therefore, the authors built the classification model for 138 Vietnamese character classes after filtering out similar character classes to increase the model's effectiveness.

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Unconstrained Offline Handwritten Word Recognition by Position Embedding Integrated ResNets Model

Cited by 26 publications

References 35 publications

Optimally configured convolutional neural network for Tamil Handwritten Character Recognition by improved lion optimization model

Optimally configured convolutional neural network for Tamil Handwritten Character Recognition by improved lion optimization model

Joint Program Partitioning and Resource Allocation for Completion Time Minimization in Multi-MEC Systems

Vietnamese character recognition based on CNN model with reduced character classes

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